1. Technical Field
The present invention relates to image segmentation, and more particularly, to image segmentation performed on multi-slice computed tomography (CT) angiography datasets.
2. Discussion of the Related Art
Cardiovascular disease, principally heart disease and stroke, is Western society's leading killer for both men and women. For example, almost one million Americans die of cardiovascular disease each year, which adds up to more than forty percent of all deaths. Moreover, heart disease does not just kill the elderly, it is the leading cause of death for all Americans age thirty-five and older. Although recent initiatives to encourage healthier lifestyles and increase early detection can prevent cardiovascular disease for those who are healthy and improve the health of people who have experienced this disease, proper diagnosis of cardiovascular disease is imperative for those afflicted.
Cardiovascular disease is typically diagnosed by a doctor who reviews a patient's medical history, health behaviors, family history, and other risk factors. If the patient has symptoms associated with, for example, heart disease, the doctor may perform a physical examination of the patient's lungs, heart and all of the blood vessels near and around the heart. Once it is determined that the patient has or is at risk of heart disease, an electrocardiogram, chest x-ray or echocardiogram is performed to determine the extent of the disease.
Although these techniques have been used for many years, they only provide a doctor with limited amounts of information. For example, x-ray and echocardiograms produce images in two-dimensions (2D) rather than in three-dimensions (3D) and the electrocardiogram records the electrical activity of the heart. Recently, however, computed tomography (CT), which is capable of producing images in 3D and four-dimensions (4D), has been used to diagnose cardiovascular disease. For example, a CT angiography may be performed to identify aneurysms in the aorta or in other major blood vessels.
A CT angiography is an examination that uses x-rays to visualize blood flow in arterial vessels throughout the body, from arteries serving the brain to those bringing blood to the lungs, kidneys, arm and legs. CT combines the use of x-rays with computerized analysis of the x-ray images. For example, beams of x-rays are passed from a rotating device through the area of interest in the patient's body from several different angles to create cross-sectional images, which are then assembled by a computer into a 3D picture of the area being studied.
In order to obtain measurements of cardiac parameters such as wall thickness of the coronary artery and ventricular volumes, segmentation of the CT images is required. For example, in order to determine the position of the aortic valve in the heart, a region growing segmentation technique in the left ventricle is performed. However, when performing a region growing in the left ventricle, the segmentation will leak through the aortic valve into other parts of the aorta. This will cause additional portions of the aorta to be segmented thus reducing the quality of the image. Although such leakage may be constrained by drawing a region around the aortic valve to restrict the segmentation algorithm from entering other parts of the aorta, this requires user interaction.
Accordingly, there is a need for an image segmentation technique that prevents leakage and that requires minimal to none user interaction thus enabling a quicker and more accurate diagnosis of cardiovascular disease.